Aerosol optical thickness (AOT) has decreased substantially in Europe in the summer half year (April–September) since 1980, with almost a 50% reduction in Central and Eastern Europe, according to Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis. At the same time, strong positive trends in ERA5 reanalysis surface solar radiation downward for all-sky and clear-sky conditions (SSRD and SSRDc, respectively) and temperature at 2 m are found for Europe in summer during the period 1979–2020. The GEBA observations show as well strong increases in SSRD during the latest four decades. Estimations of changes in SSRDc, using the Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) model, show similarly strong increases when fed by MERRA-2 AOT. The estimates of warming in this study, caused by increases in SSRD and SSRDc, are based on energy budget approximations and the Stefan Boltzmann law. The increases in near surface temperature, estimated both for clear-sky and all-sky conditions, are up to about 1°C for Central and Eastern Europe. The total warming over large parts of this region for clear-sky conditions is however nearly double the global mean temperature increase of 1.1°C, while somewhat less for all-sky conditions. The effects of aerosols on warming over the southerly Iberian Peninsula are weaker compared to countries further north. The rapid total warming over the Iberian Peninsula is probably caused by greenhouse warming, drier surface conditions, and to some degree decline in aerosols. Reduced cloud cover is found for large parts of Europe in summer during the latest four decades.

Low-cost sensors were deployed at five locations in a growing, semi-urban settlement in southwest Nigeria between June 8 and July 31, 2018 to measure particulate matter (PM_2.5 and PM₁₀), gaseous pollutants (CO, NO, NO₂, O₃ and CO₂), and meteorological variables (air temperature, relative humidity, wind speed and wind-direction). The spatial and temporal variations of measured pollutants were determined, and the probable sources of pollutants were inferred using conditional bivariate probability function (CBPF). Hourly PM_2.5 and PM₁₀ concentrations ranged from 20.7 ± 0.7 to 36.3 ± 1.6 µg m^–3 and 47.5 ± 1.5 to 102.9 ± 5.6 µg m^–3, respectively. Hourly gaseous pollutant concentrations ranged from 348 ± 132 to 542 ± 200 ppb CO, 21.5 ± 7.2 ppb NO₂ and 57.5 ± 11.3 to 64.4 ± 14.0 ppb O₃. Kruskal-Wallis ANOVA on ranks determined statistically significant spatial differences in the hourly-average pollutant concentrations. Diel variation analyses indicated that CO₂, PM_2.5, and PM₁₀ peaked in the early hours of most days, O₃ at noon while NO, NO₂, and CO peaked in the evening. Most pollutants were of anthropogenic origins and exhibited the highest contributions from the southwest at most sampling locations. There were strong similarities between pollutants source contribution at two of the monitoring sites that were in residential areas with a frequently used paved road. Mitigation strategies need to be established to avoid further deterioration of ambient air quality that negatively affect public health.

The concentrations of fine and coarse fractions of airborne particulate matter (PM) and meteorological variables (wind speed, wind direction, temperature and relative humidity) were measured at six selected locations in Ile Ife, a prominent university town in Nigeria using a network of low-cost air quality (AQ) sensor units. The objective of the deployment was to collate baseline air quality data and assess the impact of prevailing meteorological con- ditions on PM concentrations in selected residential communities downwind of an iron smelting facility. The raw data obtained from OPC-N2 of the AQ sensor units was corrected using the RH correction factor developed based k -Kohler theory. This PM (corrected) fast time resolution data (20 s) from the AQ sensor units were used to create daily averages. The overall mean mass concentrations for PM2.5 and PM10 were 213.3, 44.1, 23.8, 27.7, 20.2 and 41.5 mu g/m(3) and; 439.9, 107.1, 55.0, 72.4, 45.5 and 112.0 mu g/m(3) for Fasina (Iron -Steel Smelting Factory, ISSF), Modomo, Eleweran, Fire Service, O.A.U. staff quarters and Obafemi Awolowo University Teaching and Research Farm (OAUTRF), respectively. PM concentration and wind speed showed a negative exponential distribution curve with the lowest exponential fi t coef ficient of determination (R-2) values of 0.08 for PM2.5 and 0.03 for PM10 during nighttime periods at Eleweran and Fire service sites, respectively. The relationship between PM concen- tration and temperature gave a decay curve indicating that higher PM concentrations were observed at lower temperatures. The exponential distribution curve for the relationship between PM concentration and relative humidity (RH) showed that PM concentrations do not vary for RH 80 % while stronger relationship was noticed with higher PM concentration for RH 80 % for both day and nighttime. The performances of the MLR model were slightly poor and as such not too reliable for predicting the concentration but useful for improving predictive model accuracy when other variables contributing to the variability of PM is considered. The study concluded that the anthropogenic and industrial activities at the smelting factory contribute signi ficantly to the elevated PM mass concentration measured at the study locations.